In a dynamic model of assignment problems, small deviations suffice to move between stable outcomes. This result is used to obtain no-selection and almost-no-selection results under the stochastic stability concept for uniform and payoff-dependent errors. There is no-selection of partner or...

We develop Integer Programming (IP) solutions for some special college admission problems arising from the Hungarian higher education admission scheme. We focus on four special features, namely the solution concept of stable score-limits, the presence of lower and common quotas, and paired...

I investigate three goals of school choice: student welfare, encouraging neighborhood schools, and diversity. I develop a framework for finding the optimal match for any combination of these objectives while respecting stability and incentive compatibility. I then apply my framework to data from...

We evaluate the goal of maximizing the number of individually rational assignments. We show that it implies incentive, fairness, and implementation impossibilities. Despite that, we present two classes of mechanisms that maximize assignments. The first are Pareto efficient, and undominated –...

In ordinal (probabilistic) assignment problems, each agent reports his preference rankings over objects and receives a lottery defined over those objects. A common efficiency notion, sd-efficiency, is obtained by extending the preference rankings to preferences over lotteries by means of...

In a two-sided matching market when agents on both sides have preferences the stability of the solution is typically the most important requirement. However, we may also face some distributional constraints with regard to the minimum number of assignees or the distribution of the assignees...